The training objective of the course involves the acquisition of the following knowledge and skills:

1. Understanding the main problems related to simulation and performance analysis through random computer experiments
2. Understanding the probabilistic fundamentals underlying the theory of statistical confidence
3. Knowing how to design simple simulation programs, write the relative code, and be able to correctly interpret and represent the results obtained
4. To gain experience with a complex network simulator (Omnet++) through appropriate laboratory experiments
5. To demonstrate the knowledge of the methodologies of the course and the ability to use a simulation tool to solve a problem of interest, presenting and discussing its formulation and results

Examination methods:

The assessment of the knowledge and skills acquired is carried out through the development and presentation of a project. About half way through the course, students are offered some possible topics for a project to be developed by the end of the course, individually or in groups of 2 or 3 people. The project, which should engage every student for 40-50 hours in total, must be illustrated in a written document and presented with slides. The presentation and discussion of the project, possibly supplemented by a discussion of the homeworks, constitutes the final exam.

Assessment criteria:

The evaluation of the acquired knowledge and skills will be carried out considering:

1. The completeness and depth of the knowledge of the topics covered during the course.
2. The ability to apply the theoretical concepts treated during the course to specific practical problems
3. The ability to obtain correct numerical results in the proposed exercises
4. The ability to develop, describe and present the final project.

The course is made of 32 hours of lectures and 16 hours of laboratory activities.

Some classes are carried out using slides, which makes it easier to use complex figures. The more theoretical classes are instead carried out on the blackboard, as it is believed that this method of delivery allows to maintain the right rhythm of presentation of the topics and to keep the students more engaged. In any case, we will try to maintain an interactive teaching style, stimulating students to intervene and discuss with the teacher and with each other.

The laboratory activities are based on the Omnet++ simulator and require the student to simulate progressively more complex systems and to perform simple parametric studies through simulation.

The course includes four mandatory homeworks, which consist mainly of programming exercises and visualization of results, to verify the acquisition of the concepts developed in class and to stimulate the students to carry out practical activities.

Finally, the course includes the development of a final project whose presentation and discussion constitutes the final exam.

Additional notes about suggested reading:

The teaching material, including all the transparencies used in class, the texts that deal with the topics developed, scientific articles covered in class, exercises, datasets to be displayed, is entirely available on the website of the course on the e-learning platform.